Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda

Mekhail Mustak, Joni Salminen, Loïc Plé () and Jochen Wirtz
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Loïc Plé: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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Abstract: The rapid advancement of artificial intelligence (AI) offers exciting opportunities for marketing practice and academic research. In this study, through the application of natural language processing, machine learning, and statistical algorithms, we examine extant literature in terms of its dominant topics, diversity, evolution over time, and dynamics to map the existing knowledge base. Ten salient research themes emerge: (1) understanding consumer sentiments, (2) industrial opportunities of AI, (3) analyzing customer satisfaction, (4) electronic word-of-mouth–based insights, (5) improving market performance, (6) using AI for brand management, (7) measuring and enhancing customer loyalty and trust, (8) AI and novel services, (9) using AI to improve customer relationships, and (10) AI and strategic marketing. The scientometric analyses reveal key concepts, keyword co-occurrences, authorship networks, top research themes, landmark publications, and the evolution of the research field over time. With the insights as a foundation, this article closes with a proposed agenda for further research.

Keywords: Marketing; Artificial intelligence; AI; Natural Language Processing; Big Data; Digital (search for similar items in EconPapers)
Date: 2021-01
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Citations: View citations in EconPapers (42)

Published in Journal of Business Research, 2021, 124, pp.389-404. ⟨10.1016/j.jbusres.2020.10.044⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03269994

DOI: 10.1016/j.jbusres.2020.10.044

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